The rise in living standards increases the expectation of people in almost every field. At the forefront is health. Over the past few centuries, there have been major developments in healthcare. Medical device technology and developments in artificial intelligence (AI) are among the most important ones. The improving technology and our ability to harness the technology effectively by means such as AI have led to unprecedented advances, resulting in early diagnosis of diseases. AI algorithms enable the fast and early evaluation of images from medical devices to maximize the benefits. While developments in the field of AI were quickly adapted to the field of health, in some cases this contributed to the formation of innovative artificial intelligence algorithms. Today, the most effective artificial intelligence method is accepted as deep learning. Convolutional neural network (CNN) architectures are deep learning algorithms used for image processing. This book contains applications of CNN methods. The content is quite extensive, including the application of different CNN methods to various medical image processing problems. Readers will be able to analyze the effects of CNN methods presented in the book in medical applications.

Radiology Lecture Notes is a succinct yet thorough introduction to the essential imaging techniques used in various clinical situations. This fully revised and updated new edition presents the fundamental core knowledge of film interpretation, specialised radiological investigations, and procedures for imaging specific problems. The book explores common diseases and disorders complemented by good quality radiology images and full-colour illustrations. Concise chapters, organised by body systems cover investigations of the respiratory and gastrointestinal tracts, the cardiovascular and musculoskeletal systems, the liver and pancreas, and many others. Now in its fourth edition, this market-leading guide has been updated to reflect current practices and technologies in the field, featuring new up-to-date content on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). This practical guide: Provides a basic foundation in the principles and techniques of radiology Offers new content, including up-to-date CT, MRI and nuclear medicine images Features bulleted lists, 'Key Points' boxes, and 'Radiological Investigations' sections throughout the text Radiology Lecture Notes is an ideal study and revision guide for medical students and junior doctors, and will be a useful aid for specialist nurses, radiographers, and radiology department staff.

Choice Recommended Title, April 2021 Bioimaging: Imaging by Light and Electromagnetics in Medicine and Biology explores new horizons in biomedical imaging and sensing technologies, from the molecular level to the human brain. It explores the most up-to-date information on new medical imaging techniques, such as the detection and imaging of cancer and brain diseases. This book also provides new tools for brain research and cognitive neurosciences based on new imaging techniques. Edited by Professor Shoogo Ueno, who has been leading the field of biomedical imaging for 40 years, it is an ideal reference book for graduate and undergraduate students and researchers in medicine and medical physics who are looking for an authoritative treatise on this expanding discipline of imaging and sensing in medicine and biology. Features: Provides step-by-step explanations of biochemical and physical principles in biomedical imaging Covers state-of-the art equipment and cutting-edge methodologies used in biomedical imaging Serves a broad spectrum of readers due to the interdisciplinary topic and approach Shoogo Ueno, Ph.D, is a professor emeritus of the University of Tokyo, Tokyo, Japan. His research interests include biomedical imaging and bioelectromagnetics, particularly in brain mapping and neuroimaging, transcranial magnetic stimulation (TMS), and magnetic resonance imaging (MRI). He was the President of the Bioelectromagnetics Society, BEMS (2003-2004) and the Chairman of the Commission K on Electromagnetics in Biology and Medicine of the International Union of Radio Science, URSI (2000-2003). He was named the IEEE Magnetics Society Distinguished Lecturer during 2010 and received the d'Arsonval Medal from the Bioelectromagnetics Society in 2010.

Now in its third edition, Anatomy in Diagnostic Imaging is an unrivalled atlas of anatomy applied to diagnostic imaging. The book covers the entire human body and employs all the imaging modalities used in clinical practice; x-ray, CT, MR, PET, ultrasound and scintigraphy. An introductory chapter explains succinctly the essentials of the imaging and examination techniques drawing on the latest technical developments. In view of the great strides that have been made in this area recently, all chapters have been thoroughly revised in this third edition. The book s original and didactically convincing presentation has been enhanced with over 250 new images. There are now more than 900 images, all carefully selected in order to be user-friendly and easy-to-read, due to their high quality and the comprehensive anatomical interpretation directly placed alongside every one. Both for medical students and practising doctors, Anatomy in Diagnostic Imaging will serve as the go-to all-round reference collection linking anatomy and modern diagnostic imaging. Winner of the Radiology category at the BMA Book Awards 2015

Stochastic Modeling for Medical Image Analysis provides a brief introduction to medical imaging, stochastic modeling, and model-guided image analysis. Today, image-guided computer-assisted diagnostics (CAD) faces two basic challenging problems. The first is the computationally feasible and accurate modeling of images from different modalities to obtain clinically useful information. The second is the accurate and fast inferring of meaningful and clinically valid CAD decisions and/or predictions on the basis of model-guided image analysis. To help address this, this book details original stochastic appearance and shape models with computationally feasible and efficient learning techniques for improving the performance of object detection, segmentation, alignment, and analysis in a number of important CAD applications. The book demonstrates accurate descriptions of visual appearances and shapes of the goal objects and their background to help solve a number of important and challenging CAD problems. The models focus on the first-order marginals of pixel/voxel-wise signals and second- or higher-order Markov-Gibbs random fields of these signals and/or labels of regions supporting the goal objects in the lattice. This valuable resource presents the latest state of the art in stochastic modeling for medical image analysis while incorporating fully tested experimental results throughout.

Covers different modalities for improvement of healthcare system Describes implementation strategies and their applications in diagnosis of modalities Reviews automatic identification of related disorders using medical modality Discusses bio-potential signals and their appropriate analysis for studying different disorders Includes case studies, real-time examples and research directions

There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients. The main focus of this book is to review and summarize state-of-the-art big data and deep learning approaches to analyze and integrate multiple data types for the creation of a decision matrix to aid clinicians in the early diagnosis and identification of high risk patients for human diseases and disorders. Leading researchers will contribute original research book chapters analyzing efforts to solve these important problems.

This book highlights progress in terms of Virus Biology and Infection Detection, Prevention, and Control, along with Screening, Testing, and Detection Techniques, that will provide learners and researchers (from basic to advanced) with the most innovative computer-driven methodologies for the fight against COVID-19. In addition, this book also covers the Pre- and Post-Impact of the COVID-19 Pandemic Crisis that will definitely provide useful content for researchers to think broadly about the analytical areas affected by COVID-19. This ultimately shows different paths to the same destination to help understand the nature of the COVID-19 pandemic and how to avoid it in the future.

Revolutionary advances in imaging technology that provide high resolution, 3-D, non-invasive imaging of biological subjects have made biomedical imaging an essential tool in clinical medicine and biomedical research. Key technological advances include MRI, positron emission tomography (PET) and multidetector X-ray CT scanners. Common to all contemporary imaging modalities is the creation of digital data and pictures. The evolution from analog to digital image data is driving the rapidly expanding field of digital image analysis. Scientists from numerous disciplines now require in-depth knowledge of these complex imaging modalities. Introduction to the Science of Medical Imaging presents scientific imaging principles, introduces the major biomedical imaging modalities, reviews the basics of human and computer image analysis and provides examples of major clinical and research applications. Written by one of the world's most innovative and highly respected neuroradiologists, Introduction to the Science of Medical Imaging is a landmark text on image acquisition and interpretation.

This book explores novel methods for implementing X-ray diffraction technology as an imaging modality, which have been made possible through recent breakthroughs in detector technology, computational power, and data processing algorithms. The ability to perform fast, spatially-resolved X-ray diffraction throughout the volume of a sample opens up entirely new possibilities in areas such as material analysis, cancer diagnosis, and explosive detection, thus offering the potential to revolutionize the fields of medical, security, and industrial imaging and detection. Featuring chapters written by an international selection of authors from both academia and industry, the book provides a comprehensive discussion of the underlying physics, architectures, and applications of X-ray diffraction imaging that is accessible and relevant to neophytes and experts alike. Teaches novel methods for X-ray diffraction imaging Comprehensive and self-contained discussion of the relevant physics, imaging techniques, system components, and data processing algorithms Features state-of-the-art work of international authors from both academia and industry. Includes practical applications in the medical, industrial, and security sectors

This book examines the use of biomedical signal processing-EEG, EMG, and ECG-in analyzing and diagnosing various medical conditions, particularly diseases related to the heart and brain. In combination with machine learning tools and other optimization methods, the analysis of biomedical signals greatly benefits the healthcare sector by improving patient outcomes through early, reliable detection. The discussion of these modalities promotes better understanding, analysis, and application of biomedical signal processing for specific diseases. The major highlights of Biomedical Signal Processing for Healthcare Applications include biomedical signals, acquisition of signals, pre-processing and analysis, post-processing and classification of the signals, and application of analysis and classification for the diagnosis of brain- and heart-related diseases. Emphasis is given to brain and heart signals because incomplete interpretations are made by physicians of these aspects in several situations, and these partial interpretations lead to major complications. FEATURES Examines modeling and acquisition of biomedical signals of different disorders Discusses CAD-based analysis of diagnosis useful for healthcare Includes all important modalities of biomedical signals, such as EEG, EMG, MEG, ECG, and PCG Includes case studies and research directions, including novel approaches used in advanced healthcare systems This book can be used by a wide range of users, including students, research scholars, faculty, and practitioners in the field of biomedical engineering and medical image analysis and diagnosis.

The Handbook of Neurophotonics provides a dedicated overview of neurophotonics, covering the use of advanced optical technologies to record, stimulate, and control the activity of the brain, yielding new insight and advantages over conventional tools due to the adaptability and non-invasive nature of light. Including 30 colour figures, this book addresses functional studies of neurovascular signaling, metabolism, electrical excitation, and hemodynamics, as well as clinical applications for imaging and manipulating brain structure and function. The unifying theme throughout is not only to highlight the technology, but to show how these novel methods are becoming critical to breakthroughs that will lead to advances in our ability to manage and treat human diseases of the brain. Key Features: Provides the first dedicated book on state-of-the-art optical techniques for sensing and imaging across at the cellular, molecular, network, and whole brain levels. Highlights how the methods are used for measurement, control, and tracking of molecular events in live neuronal cells, both in basic research and clinical practice. Covers the entire spectrum of approaches, from optogenetics to functional methods, photostimulation, optical dissection, multiscale imaging, microscopy, and structural imaging. Includes chapters that show use of voltage-sensitive dye imaging, hemodynamic imaging, multiphoton imaging, temporal multiplexing, multiplane microscopy, optoacoustic imaging, near-infrared spectroscopy, and miniature neuroimaging devices to track cortical brain activity.

Computer-aided design (CAD) plays a key role in improving biomedical systems for various applications. It also helps in the detection, identification, predication, analysis, and classification of diseases, in the management of chronic conditions, and in the delivery of health services. This book discusses the uses of CAD to solve real-world problems and challenges in biomedical systems with the help of appropriate case studies and research simulation results. Aiming to overcome the gap between CAD and biomedical science, it describes behaviors, concepts, fundamentals, principles, case studies, and future directions for research, including the automatic identification of related disorders using CAD. Features: Proposes CAD for the study of biomedical signals to understand physiology and to improve healthcare systems' ability to diagnose and identify health disorders. Presents concepts of CAD for biomedical modalities in different disorders. Discusses design and simulation examples, issues, and challenges. Illustrates bio-potential signals and their appropriate use in studying different disorders. Includes case studies, practical examples, and research directions. Computer-Aided Design and Diagnosis Methods for Biometrical Applications is aimed at researchers, graduate students in biomedical engineering, image processing, biomedical technology, medical imaging, and health informatics.

"This book presents the technology evaluation methodology from the point of view of radiological physics and contrasts the purely physical evaluation of image quality with the determination of diagnostic outcome through the study of observer performance. The reader is taken through the arguments with concrete examples illustrated by code in R, an open source statistical language." - from the Foreword by Prof. Harold L. Kundel, Department of Radiology, Perelman School of Medicine, University of Pennsylvania "This book will benefit individuals interested in observer performance evaluations in diagnostic medical imaging and provide additional insights to those that have worked in the field for many years." - Prof. Gary T. Barnes, Department of Radiology, University of Alabama at Birmingham This book provides a complete introductory overview of this growing field and its applications in medical imaging, utilizing worked examples and exercises to demystify statistics for readers of any background. It includes a tutorial on the use of the open source, widely used R software, as well as basic statistical background, before addressing localization tasks common in medical imaging. The coverage includes a discussion of study design basics and the use of the techniques in imaging system optimization, memory effects in clinical interpretations, predictions of clinical task performance, alternatives to ROC analysis, and non-medical applications. Dev P. Chakraborty, PhD, is a clinical diagnostic imaging physicist, certified by the American Board of Radiology in Diagnostic Radiological Physics and Medical Nuclear Physics. He has held faculty positions at the University of Alabama at Birmingham, University of Pennsylvania, and most recently at the University of Pittsburgh.

This book provides an accessible yet rigorous introduction to topology and homology focused on the simplicial space. It presents a compact pipeline from the foundations of topology to biomedical applications. It will be of interest to medical physicists, computer scientists, and engineers, as well as undergraduate and graduate students interested in this topic. Features: Presents a practical guide to algebraic topology as well as persistence homology Contains application examples in the field of biomedicine, including the analysis of histological images and point cloud data

The aim of this book is to outline the concept of entropy, various types of entropies and their implementation to evaluate a variety of biomedical signals/images. The book emphasizes various entropy-based image pre-processing methods which are essential for the development of suitable computerized examination systems. The recent research works on biomedical signal evaluation confirms that signal analysis provides vital information regarding the physiological condition of the patient, and the efficient evaluation of these signals can help to diagnose the nature and the severity of the disease. This book emphasizes various entropy-based image pre-processing methods which are essential for the development of suitable computerized examination systems for the analysis of biomedical images recorded with a variety of modalities. The work discusses the image pro-processing methods with the Entropies, such as Kapur, Tsallis, Shannon and Fuzzy on a class of RGB-scaled and gray-scaled medical pictures. The performance of the proposed technique is justified with the help of suitable case studies, which involves x-ray image analysis, MRI analysis and CT analysis. This book is intended for medical signal/image analysts, undergraduate and postgraduate students, researchers, and medical scientists interested in biomedical data evaluation.

In view of better results expected from examination of medical datasets (images) with hybrid (integration of thresholding and segmentation) image processing methods, this work focuses on implementation of possible hybrid image examination techniques for medical images. It describes various image thresholding and segmentation methods which are essential for the development of such a hybrid processing tool. Further, this book presents the essential details, such as test image preparation, implementation of a chosen thresholding operation, evaluation of threshold image, and implementation of segmentation procedure and its evaluation, supported by pertinent case studies. Aimed at researchers/graduate students in the medical image processing domain, image processing, and computer engineering, this book: Provides broad background on various image thresholding and segmentation techniques Discusses information on various assessment metrics and the confusion matrix Proposes integration of the thresholding technique with the bio-inspired algorithms Explores case studies including MRI, CT, dermoscopy, and ultrasound images Includes separate chapters on machine learning and deep learning for medical image processing

This timely overview of dose, benefit, and risk in medical imaging explains to readers how to apply this information for informed decision-making that improves patient outcomes. The chapters cover patient and physician perspectives, referral guidelines, appropriateness criteria, and quantifying medical imaging benefits. The authors have included essential discussion about radiologic physics in medical imaging, fundamentals of dose and image quality, risk assessment, and techniques for optimization and dose reduction. The book highlights practical implementation aspects with useful case studies and checklists for treatment planning. Clinicians, students, residents, and professionals in medical physics, biomedical engineering, radiology, oncology, and allied disciplines will find this book an essential resource with the following key features: Discusses risk, benefit, dose optimization, safety, regulation, radiological protection, and shared & informed decision-making. Covers regulatory oversight by government agencies, manufacturers, and societies. Highlights best practices for improving patient safety and outcomes. Gives guidelines on doses associated with specific procedures.

Basic Guide to Dental Radiography provides an essential introduction to radiography in the dental practice. Illustrated throughout, this guide outlines and explains each topic in a clear and accessible style. * Comprehensive coverage includes general physics, principles of image formation, digital image recording, equipment, biological effects of x-rays and legislation * Suitable for the whole dental team * Illustrated in full colour throughout * Ideal for those completing mandatory CPD in radiography * Useful study guide for the NEBDN Certificate in Dental Radiography, the National Certificate in Radiography or the Level 3 Diploma in Dental Nursing

Highly Commended at the British Medical Association Book Awards 2016 MRI at a Glance encapsulates essential MRI physics knowledge. Illustrated in full colour throughout, its concise text explains complex information, to provide the perfect revision aid. It includes topics ranging from magnetism to safety, K space to pulse sequences, and image contrast to artefacts. This third edition has been fully updated, with revised diagrams and new pedagogy, including 55 key points, tables, scan tips, equations, and learning points. There is also an expanded glossary and new appendices on optimizing image quality, parameters and trade-offs. A companion website is also available at www.ataglanceseries.com/mri featuring animations, interactive multiple choice questions, and scan tips to improve your own MRI technique. MRI at a Glance is ideal for student radiographers and MRI technologists, especially those undertaking the American Registry of Radiation Technologist (ARRT) MRI examination, as well as other health professionals involved in MRI.

This updated edition of the leading text on the imaging of child abuse and its imitators combines radiographic images with pathologic correlates of inflicted injuries. Presented in full color for the first time, it contains many new photomicrographs and clinical images of bone scintigraphy, CT, MRI and sonography. Presenting radiologic findings in clinical, biomechanical and medicolegal contexts, a wealth of new material relating to extremity, thoracic, spinal and intracranial injuries is included. Chapters on intracranial (extra-axial and parenchymal), visceral and miscellaneous injuries, and MRI physics have been revised and expanded, while new chapters cover disorders of calcium and phosphorus metabolism and an extended discussion of skeletal injury. Complete with technical discussions explaining the physical principles and instrumentation of imaging equipment, this is essential reading for radiologists, pediatricians, forensic pathologists and emergency room physicians. Additionally, it will be of interest to a wide array of legal professionals.

The ECG is one of the most commonly used investigations in contemporary medicine. Interpretation of the ECG can appear daunting, but it is actually relatively straightforward as long as a systematic approach is taken. Pocket ECGs for Nurses assists with this task by providing a detailed yet readable introduction to ECG interpretation, supplemented by clinical information about how to act based on its findings. The book begins by covering the basics of cardiac anatomy and physiology and how these relate to the ECG. It then guides nurses on how to perform a high-quality ECG recording, interpret it and make sense of common ECG abnormalities. The book also includes a guide to ambulatory and bedside monitoring as well as useful chapter summaries. This pocketbook is an essential reference for the non-specialist who needs to be able to record and perform a basic and safe interpretation of an ECG. Written in plain language with clear explanations, bullet lists and summaries throughout, this handy guide will benefit nurses as well as paramedics and other allied health professionals in recording and reading ECGs.

Radioembolization is a widely used treatment for non-resectable primary and secondary liver cancer. This handbook addresses the radiation biology, physics, nuclear medicine, and imaging for radioembolization using Yttrium-90 (90Y) microspheres, in addition to discussing aspects related to interventional radiology. The contents reflect on and off-label treatment indications, dose-response relationships, treatment-planning, therapy optimization, radiation safety, imaging follow-up and many other facets of this therapy necessary for both novice and advanced users alike.

Choice Recommended Title, January 2021 This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective

Understand Quantitative Radiobiology from a Radiation Biophysics Perspective In the field of radiobiology, the linear-quadratic (LQ) equation has become the standard for defining radiation-induced cell killing. Radiotherapy Treatment Planning: Linear-Quadratic Radiobiology describes tumor cell inactivation from a radiation physics perspective and offers appropriate LQ parameters for modeling tumor and normal tissue responses. Explore the Latest Cell Killing Numbers for Defining Iso-Effective Cancer Treatments The book compiles radiation mechanism information from biophysical publications of the past 50 years, addressing how ionizing radiation produces the killing of stem cells in human tumors. It presents several physical and chemical parameters that can modulate the radiation response of clonogenic cells in tumors. The authors describe the use of the LQ model in basic radiation mechanism studies with cells of relatively homogeneous radiation response and then extend the model to the fitting of survival data generated with heterogeneous cell populations (tumors). They briefly discuss how to use the LQ model for predicting tumor (local) control probability (TCP) and normal tissue complication probability (NTCP). The book also examines potential molecular targets related to alpha- and beta-inactivation and gives suggestions for further molecular characterizations of these two independent processes. Develop Efficacious, Patient-Friendly Treatments at Reduced Costs Focusing on quantitative radiobiology in LQ formulation, this book assists medical physicists and radiation oncologists in identifying improved cancer treatments. It also encourages investigators to translate potentially improved radiotherapy schedules based on TCP and NTCP modeling into actual patient benefit.